个人简介

王鹏焜，中国科大软件学院特任副研究员，硕士生导师。2017年本科毕业于吉林大学软件学院，2023年博士毕业于中国科学技术大学大数据学院。主要研究方向为泛化深度学习、时空数据挖掘等，致力于提升深度学习模型的泛化性与鲁棒性，并应用于交叉学科（城市科学、化学材料）等开放场景，推动深度学习模型快速落地。近五年来共发表高水平论文17篇，其中第一/通讯作者身份5篇，包括IEEE TKDE，IEEE TVT等。多次担任NeurIPS、KDD、AAAI等在内的CCF-A类会议审稿人。

电子邮箱：

pengkun@ustc.edu.cn

联系地址：

江苏省苏州市工业园区若水路99号至德楼A楼1302-2

个人主页：

http://home.ustc.edu.cn/~pengkun/

主要研究方向

泛化深度学习理论（长尾学习、分布外泛化等）

开放环境下时空数据挖掘（持续学习、联邦学习等）

面向交叉学科的泛化深度学习

获奖情况

2021年，姑苏优秀学生奖学金

2021年，光华奖学金

2021年，“赢在苏州，创赢未来”苏州市青年精英创业大赛一等奖

2022年，全球华人大学生数据应用创新大赛铜奖

学术论文及著作

[1]     Pengkun Wang, Chuancai Ge, Zhengyang Zhou, Xu Wang, Yuantao Li, Yang Wang*, Joint Gated Co-attention Based Multi-modal Networks for Subregion House Price Prediction, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2021. (CCF-A, IF=8.9)

[2]     Pengkun Wang, Chaochao Zhu, Xu Wang, Zhengyang Zhou, Guang Wang, Yang Wang*, Inferring Intersection Traffic Patterns with Sparse Video Surveillance Information: An ST-GAN Method, IEEE Transactions on Vehicular Technology (IEEE TVT), 2022. (JCR一区, IF=6.8)

[3]     Pengkun Wang, Xu Wang, Binwu Wang, Yudong Zhang, Lei Bai*, Yang Wang*, Long-tailed Time Series Classification via Feature Space Rebalancing, The International Conference on Database Systems for Advanced Applications (DASFAA), 2023. (CCF-B)

[4]     Pengkun Wang, Xu Wang, Binwu Wang, Yudong Zhang, Lei Bai*, Yang Wang*, Countering Modal Redundancy and Heterogeneity: A Self-Correcting Multimodal Fusion, IEEE International Conference on Data Mining (ICDM), 2022. (CCF-B)

[5]     Yudong Zhang, Wei Lu, Xu Wang, Pengkun Wang*, Yang Wang*, Pondering about Task Spatial Misalignment: Classification-Localization Equilibrated Object Detection, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023. (CCF-B, 共同通信作者)

[6]     Xu Wang, Hongbo Zhang, Pengkun Wang, Yudong Zhang, Binwu Wang, Zhengyang Zhou, Yang Wang*, An Observed Value Consistent Diffusion Model for Imputing Missing Values in Multivariate Time Series, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023. (CCF-A)

[7]     Binwu Wang, Yudong Zhang, Xu Wang, Pengkun Wang, Zhengyang Zhou, Lei Bai, Yang Wang*, Pattern Expansion and Consolidation for Continual Traffic Prediction with Expanding Graphs, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023. (CCF-A)

[8]     Kuo Yang, Zhengyang Zhou, Wei Sun, Pengkun Wang, Xu Wang, Yang Wang*, EXTRACT and REFINE: Finding A Support Subgraph Set for Graph Representation, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023. (CCF-A)

[9]     Kun Wang, Yuxuan Liang*, Pengkun Wang, Xu Wang, Pengfei Gu, Junfeng Fang, Yang Wang*, Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective, International Conference on Learning Representations (ICLR), 2023. (机器学习领域顶级会议)

[10]  Binwu Wang, Yudong Zhang, Jiahao Shi, Pengkun Wang, Xu Wang, Lei Bai*, Yang Wang*, Knowledge Expansion and Consolidation for Continual Traffic Prediction with Expanding Graphs, IEEE Transactions on Intelligent Transportation Systems (IEEE TITS), 2023. (CCF-B, 中科院一区, IF=8.5)

[11]  Binwu Wang, Yudong Zhang, Pengkun Wang, Xu Wang, Lei Bai*, Yang Wang*, A Knowledge-Driven Memory System for Traffic Flow Prediction, The International Conference on Database Systems for Advanced Applications (DASFAA), 2023. (CCF-B)

[12]  Xu Wang, Lianliang Chen, Hongbo Zhang, Pengkun Wang, Zhengyang Zhou, Yang Wang*, A Multi-graph Fusion Based Spatiotemporal Dynamic Learning Framework, ACM International Conference on Web Search and Data Mining (WSDM), 2023. (CCF-B)

[13]  Kun Wang, Zhengyang Zhou, Xu Wang, Pengkun Wang, Qi Fang, Yang Wang*, A2DJP: A Two Graph-based Component Fused Learning Framework for Urban Anomaly Distribution and Duration Joint-Prediction, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2022. (CCF-A, IF=8.9)

[14]  周正阳, 刘浩, 王琨, 王鹏焜, 王旭, 汪炀*, 基于教师-学生时空半监督网络的城市事件预测方法, 电子学报, 2022. (CCF-A 中文)

[15]  干创, 吴桂兴*, 詹庆原, 王鹏焜, 彭志磊, 基于骨架模态的多级门控图卷积动作识别网络, 计算机科学, 2022. (CCF-B 中文)

[16]  Wen Zhang, Zhengyang Zhou, Chuancai Ge, Pengkun Wang, Data-driven Vehicular Communications in Urban Vehicular Network, International Conference on Communication Software and Networks (ICCSN), 2019.

[17]  Zhengyang Zhou, Lianliang Chen, Chaochao Zhu, Pengkun Wang, Stack ResNet For Short-term Accident Risk Prediction Leveraging Cross-domain Data, China Automation Congress (CAC), 2019.